Patient-Perceived Impact of the COVID-19 Pandemic on Medication Adherence and Access to Care for Long-Term Diseases: A Cross-Sectional Online Survey
Bibliographic record
Abstract
The COVID-19 pandemic has been associated with lifestyle changes, reduced access to care and potential impacts on medication self-management. Our main objectives are to evaluate the impact of the pandemic on patient adherence and access to care and long-term medications and determine its association with sociodemographic and clinical factors. This study is part of the Specchio-COVID-19 longitudinal cohort study in Geneva, Switzerland, conducted through an online questionnaire. Among the 982 participants (median age: 56; 61% female), 827 took long-term medications. There were 76 reported changes in medication dosages, of which 24 (31%) were without a physician’s recommendation, and 51 delays in initiation or premature medication interruptions, of which 24 (47%) were without a physician’s recommendation. Only 1% (9/827) of participants faced medication access issues. Participants taking a respiratory medication had a four-times greater odds of reporting more regular medication (OR = 4.27; CI 95%: 2.11–8.63) intake, whereas each year increase in age was significantly associated with 6% fewer relative risks of discontinuation (OR = 0.94; CI 95%: 0.91–0.97) and 3% fewer relative risks of changes in medication dosage (OR = 0.97; CI 95%: 0.95–1.00). Despite the limited impact of the pandemic on adherence and access to medications, our results emphasize the need for understanding patient challenges when self-managing their long-term medication, notably during public health crises.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".